Countly Mobile Analytics | Blog

Dec 04

Query mobile data with Countly Drill

What a fantastic week! We listened you and worked hard to provide you the best-of-breed data query and analytics tool, Countly Drill. This powerful tool gives you the opportunity to perform advanced segmentations on your data using AND, OR and BY filters. Other features of Drill include, but not limited to: 

As an example, let’s have a look at the result of “I want to see the breakdown of users watching TV by platform”, which is very easy to grab. Here’s the output retrieved in seconds: 


One very powerful feature is the bookmarks - with this tool, you do not have to remember your queries, but only retrieve from your latest bookmarks:


Drill is now available for all Cloud users and Enterprise customers. You can access Drill - even if you have a free account - right from the main menu. 

Your custom events have been collected by Drill by some time now, so why don’t you login and start experimenting yourself? 

— Countly Team

Nov 16

Your trust is our business

For the last one year, Countly has been the platform of choice for mobile developers and product managers. Roughly more than one year has passed since our first version, but we already conquered 96 countries, 1000+ servers, 5000 apps and hundreds of happy customers. Countly powered apps run on a whopping 100M+ devices already.

Thank you. You made our dream a reality!

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Nov 11

Analyzing Skyward Slots moblie app with Countly - a case study

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Sidebolt is a game studio in Dublin Ohio, with a mission to develop fun and innovative games. We were thrilled with their newest game, Skyward Slots for iOS and wanted to learn how Sidebolt satisfies its mobile analytics needs using Countly.

Q: How was your experience while developing Skyward Slots?

With Skyward Slots we wanted to make something new. We wanted to raise the bar on what a slots game could be, we didn’t want it to feel like a typical slots game. We also wanted our users to be able to seamlessly move from device to device. With the explosion of mobile, it’s typical for players to have multiple devices and they expect to be able to pick up any one of them and just play. So for us that meant building our own private cloud and running Skyward Slots from our servers so players weren’t tied to a single device.

To stand up our private cloud, we used a systems and cloud infrastructure automation framework called Chef. To keep the cost curve down we deployed on commodity hardware built in house and found that IKEA’s filing cabinets make great enclosures for micro ATX servers. 

Once our infrastructure was deployed we began work on the server game code and front end. The front end was written in Objective-C using the cocos2d graphics library.

Q: Why did you choose Countly as your mobile analytics platform? 

We were looking for a quick and easy solution for analytics that we could interface with from our own servers. Countly quickly stood out with its easy to read and navigate dashboard and simple server side API. Countly made the process of storing and analyzing large amounts of data simple and painless, also it’s just so good looking!

Q: Which feature do you like most in Countly?

Countly gives us a full view of our application and how our players interact with it. It answers player engagement questions so that we can better focus our efforts on areas our players use the most. There are a ton of great features in Countly but for us the stand outs are Events, Engagement and the server API. Events allow us to answer questions like “How many users disable the in-game tutorial”, or “What is the most popular mini-game”. These questions allow us to test our assumptions and guide future development which saves us time. The Engagement view gives us insight into player loyalty and session patterns. The server API allowed us to communicate with Countly directly from our game servers and control the flow of data.

Q: What is the single feature you want to get implemented?

We would love to see per user analytics. It would be great to drill into a player and view additional metrics on that player’s session. This would allow us to build a profile of certain types of users and ask additional questions such as “What are the play habits of users who have made purchases” or “Of our most active players what are the most/least triggered Events”. 

Q: Can you give some hints about your upcoming titles and work? 

We are actively working on new content for Skyward Slots but we’ve also started brainstorming our next game which will leverage our new backend infrastructure.

We’d like to thank to Conor Seabrook from SideBolt for this exciting interview.

Oct 04

Game Analytics: Interview with field experts

When we first saw the Game Analytics: Maximizing the Value of Player Data book, we were very excited to see such a valuable printed material which gathers exclusive experience of field workers. We had several questions in mind, and asked authors - Magy Seif El-Nasr, Anders Drachen and Alessandro Canossa our questions. They kindly replied and here’s the result of this nice interview. 

Note that this book is available from the publisher Springer-Verlag, as well as several distributors like Amazon.

Enjoy! :-)

Game analytics is like an iceberg - what lies beneath is often misunderstood and unknown at its best. What is Game Analytics?

Let’s first get some definitions in place: While the terminology remains somewhat shaky, analytics is fundamentally a process that is grounded in analysis of data to derive results that can inform or shape theories about a phenomenon. It is composed of a large group of theories, methods, processes, architectures and technologies that are used to transform raw data into meaningful information. This information used in the cycle of game production can support decision-making regarding business, project development, design, etc. Analytics is the *process* of discovery and communication of patterns in data towards solving problems and producing results that can drive action, improve performance, support decision making, decide on monetization strategies, support game design etc. - or just because it is fun!

Game analytics is a term we use to denote the specific application of analytics to games. It is important to realize the analytics is about more than just the users, or in the case of game analytics, the players. It looks at games both as products and as projects. As a product, important areas of focus are user experience, behavior and monetization. 

How does game analytics help developers drive revenue? 

Being data-driven - if done right - means for a company that it has solid ground on which to make decisions (does not guarantee the right decisions are made). This is what can be used to increase revenue in a number of ways, e.g. optimizing retention or increasing internal effectiveness. This is the way analytics can drive revenue in the broadest sense. 

Analytics can be a direct driver of innovation as well, but more commonly act in a supporting role - similar to how analytics can support design.

Talking about analytics in general, what does it require to understand and engage customers? [in terms of technology, talent, domain expertise and knowledge] 

Our book, Game Analytics: Maximizing the Value of Player Data, discusses parts of this process. But as discussed above, we are just in the beginning of investigating the value of the current methods and the need to establish new methods to look into users’ behaviors accounting for context and users’ individual differences. 

Do you think analyzing the end user behavior could be considered a sort of art? Or is something closer to making business and money?

Claiming that analyzing player behavior is an art entails admitting that it is a purely subjective practice and not reproducible or generalizable. Game analytics as a field has been seen as a scientifically driven method that can be used to derive business decisions and can inform design. The process of analyzing the data to derive design decisions, however, is more of a creative process that requires science and art, as if you treat it as a completely objective process, you would overlook the significant human element that is involved in most forms of data mining. Thus, we would say that game analytics as a process informing design is a craft: in between art and science.

What are the daily tasks for a game analyst? What is it like to be a game analyst? 

There are many kinds of analysts working with games, or more specifically analysts operating with different goals. For example, some analysts are monetization specialists and focus on in-game economic analysis, while others analyze markets to inform management and marketing. Larry Mellon, one of the most respected people in the field, noted that game analytics tends to focus on the process of developing games, the performance of technical infrastructure, or the players. There is a tendency to equate game analytics with the analysis of player behavior, but this is just one component of analytics for games. 

But, if we focus on those analysts who work with player behavior (i.e. also customer behavior), their primary duties (and we are heavily generalizing here!) revolve around establishing data collection infrastructure, acquiring and storing data, pre-processing and otherwise readying data for analysis, analyzing player data, visualizing and reporting results, and – importantly – communicating these results to a variety of stakeholders. The kind of knowledge game analysts can draw on to solve these challenges ranges from statistics, machine learning, psychology, design, visualization, communication, various other Sciences, and beyond.

Predictive analytics is often mentioned when people talk about analytics and games. How can predictive behavioral analysis help a game developer?

If we focus on the specific aspect of game analytics that deal with the people who play games, there are at least two ways we can view them: as players or as customers. The first perspective focuses on investigating how the game is played and trying to inform game design as a result, the second perspective focuses on investigating monetization channels and trying to inform how to design revenue funnels (we are generalizing a lot here).

Predictive analytics is applicable in both cases, with the general purpose of trying to forecast what all, groups of or any one individual player might do in the future. Typical applications of predictive techniques involve predicting when a player might leave a game, or when a non-paying user becomes a paying user. However, using predictive analytics to evaluate design is also common. 

What are the difficulties and challenges in today’s game analytics world? 

There are multiple challenges facing game analytics as a field. The process of game analytics is composed of various steps each has its own challenges. These steps include: data collection, data analysis, abstraction of data to develop a narrative delivered to different stakeholders.

Challenges to data collection include selection of features to collect, more challenges of sampling, storage, and retrieval. Challenges to data analysis involves the development of algorithms that will establish better understanding of the data given the variable and changing nature of the game itself that constitute the context within which data is collected. While methods have been developed to investigate analysis and collection techniques, less research has been developed on the abstraction and narrativisation step. 

Sep 24

Countly meetups in US: Come see us in NY, Boston, SF

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Hi Countly fans!

We are having a long trip to US to meet with potential customers and investors, between 29 September - 16 October. This is our definitive schedule: 

 - New York: 29 September - 2 October

 - Boston: 2 October - 5 October

 - San Francisco: 5 October - 16 October

If you are nearby and want to talk about Countly, mobile analytics and anything related, just drop us a note. We’d be happy to meet with you in one of our locations.

— Countly Team